Processing‐History‐Programmed Silk Fibers Integrating Mechanical Robustness, Ionic Conduction, and Optical Waveguiding for Intelligent Wearables

ABSTRACT Soft fibrous materials that integrate mechanical robustness with efficient electrical and optical signal transport are highly desirable for intelligent wearables, yet remain challenging due to the intrinsic trade‐off between structural reinforcement and functional transport. Here, inspired by natural silk spinning, we introduce a processing‐history programming strategy that exploits the controlled coupling of humidity, stretching, and dehydration to encode multifunctionality into silk‐based fibers without chemical modification. Through a humidity‐assisted stretching‐mediated spinning (SMS) pathway, hierarchical structural reconstruction is synchronously induced, featuring enhanced β‐sheet formation, increased axial orientation, and a radially graded architecture, which together lead to orders‐of‐magnitude improvements in strength, modulus, and toughness. Importantly, the mechanically reinforced fibers preserve continuous ionic transport pathways and exhibit stable electromechanical responses, while also functioning as visible‐light waveguides with optical transmission. By integrating multimodal electrical and optical signals with on‐device machine learning, the fibers enable real‐time decoding of human motion states and sweat electrolyte concentrations, establishing processing‐history programming as a general paradigm for designing multifunctional fibrous electronics and intelligent textiles.